Comorbidity Indices Versus Function as Potential Predictors of 30-Day Readmission in Older Patients Following Postacute Rehabilitation

Amit Kumar, Amol Karmarkar, James E. Graham, Linda Resnik, Alai Tan, Anne Deutsch, Kenneth Ottenbacher

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

BACKGROUND: Information regarding the association of comorbidity indices with readmission risk for older adults receiving postacute care is limited. The purpose of this study was to compare the discriminatory ability of five comorbidity indices in predicting 30-day all-cause hospital readmission following discharge to the community from postacute inpatient rehabilitation facilities (IRF).

METHODS: The sample included Medicare fee-for-service beneficiaries with stroke, lower extremity joint replacement, and fracture, discharged from IRF in 2011 (N = 75,582). Logistic regression models were used to predict 30-day all-cause readmission. Impairment-specific base models included demographic characteristics and length of stay. Subsequent models included individual comorbidity indices: Tier, Charlson, Elixhauser, functional comorbidity index (FCI), and the hierarchical condition category (HCC). We then added discharge functional status to each model. Results were compared using C-statistics.

RESULTS: Thirty-day readmission rates following discharge from an IRF ranged from 6.5% (joint replacement) to 14% (stroke). The C-statistics were 0.53, 0.56, and 0.55 for the base models in the stroke, joint replacement, and fracture groups, respectively. Adding the Tier, Charlson, FCI, or Elixhauser variables increased the C-statistics by 0.03-0.07 across the three impairment categories. Adding the HCC increased the C-statistics by 0.06-0.09. With the addition of discharge functional status in the model, the C-statistics further increased by 0.06-0.09.

CONCLUSIONS: Comorbidity indices were weakly associated with 30-day readmission in older adults discharged from postacute inpatient rehabilitation. Adding patient-level functional status to the comorbidity indices further improved the discriminatory ability to predict readmission in our sample.

Original languageEnglish (US)
Pages (from-to)223-228
Number of pages6
JournalThe journals of gerontology. Series A, Biological sciences and medical sciences
Volume72
Issue number2
DOIs
StatePublished - Feb 1 2017

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Comorbidity
Rehabilitation
Replacement Arthroplasties
Inpatients
Stroke
Subacute Care
Logistic Models
Fee-for-Service Plans
Patient Readmission
Medicare
Lower Extremity
Length of Stay
Demography

Keywords

  • Comorbidity Index
  • Hospital readmission
  • Medicare
  • Postacute care
  • Risk prediction

ASJC Scopus subject areas

  • Aging
  • Geriatrics and Gerontology

Cite this

Comorbidity Indices Versus Function as Potential Predictors of 30-Day Readmission in Older Patients Following Postacute Rehabilitation. / Kumar, Amit; Karmarkar, Amol; Graham, James E.; Resnik, Linda; Tan, Alai; Deutsch, Anne; Ottenbacher, Kenneth.

In: The journals of gerontology. Series A, Biological sciences and medical sciences, Vol. 72, No. 2, 01.02.2017, p. 223-228.

Research output: Contribution to journalArticle

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title = "Comorbidity Indices Versus Function as Potential Predictors of 30-Day Readmission in Older Patients Following Postacute Rehabilitation",
abstract = "BACKGROUND: Information regarding the association of comorbidity indices with readmission risk for older adults receiving postacute care is limited. The purpose of this study was to compare the discriminatory ability of five comorbidity indices in predicting 30-day all-cause hospital readmission following discharge to the community from postacute inpatient rehabilitation facilities (IRF).METHODS: The sample included Medicare fee-for-service beneficiaries with stroke, lower extremity joint replacement, and fracture, discharged from IRF in 2011 (N = 75,582). Logistic regression models were used to predict 30-day all-cause readmission. Impairment-specific base models included demographic characteristics and length of stay. Subsequent models included individual comorbidity indices: Tier, Charlson, Elixhauser, functional comorbidity index (FCI), and the hierarchical condition category (HCC). We then added discharge functional status to each model. Results were compared using C-statistics.RESULTS: Thirty-day readmission rates following discharge from an IRF ranged from 6.5{\%} (joint replacement) to 14{\%} (stroke). The C-statistics were 0.53, 0.56, and 0.55 for the base models in the stroke, joint replacement, and fracture groups, respectively. Adding the Tier, Charlson, FCI, or Elixhauser variables increased the C-statistics by 0.03-0.07 across the three impairment categories. Adding the HCC increased the C-statistics by 0.06-0.09. With the addition of discharge functional status in the model, the C-statistics further increased by 0.06-0.09.CONCLUSIONS: Comorbidity indices were weakly associated with 30-day readmission in older adults discharged from postacute inpatient rehabilitation. Adding patient-level functional status to the comorbidity indices further improved the discriminatory ability to predict readmission in our sample.",
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N2 - BACKGROUND: Information regarding the association of comorbidity indices with readmission risk for older adults receiving postacute care is limited. The purpose of this study was to compare the discriminatory ability of five comorbidity indices in predicting 30-day all-cause hospital readmission following discharge to the community from postacute inpatient rehabilitation facilities (IRF).METHODS: The sample included Medicare fee-for-service beneficiaries with stroke, lower extremity joint replacement, and fracture, discharged from IRF in 2011 (N = 75,582). Logistic regression models were used to predict 30-day all-cause readmission. Impairment-specific base models included demographic characteristics and length of stay. Subsequent models included individual comorbidity indices: Tier, Charlson, Elixhauser, functional comorbidity index (FCI), and the hierarchical condition category (HCC). We then added discharge functional status to each model. Results were compared using C-statistics.RESULTS: Thirty-day readmission rates following discharge from an IRF ranged from 6.5% (joint replacement) to 14% (stroke). The C-statistics were 0.53, 0.56, and 0.55 for the base models in the stroke, joint replacement, and fracture groups, respectively. Adding the Tier, Charlson, FCI, or Elixhauser variables increased the C-statistics by 0.03-0.07 across the three impairment categories. Adding the HCC increased the C-statistics by 0.06-0.09. With the addition of discharge functional status in the model, the C-statistics further increased by 0.06-0.09.CONCLUSIONS: Comorbidity indices were weakly associated with 30-day readmission in older adults discharged from postacute inpatient rehabilitation. Adding patient-level functional status to the comorbidity indices further improved the discriminatory ability to predict readmission in our sample.

AB - BACKGROUND: Information regarding the association of comorbidity indices with readmission risk for older adults receiving postacute care is limited. The purpose of this study was to compare the discriminatory ability of five comorbidity indices in predicting 30-day all-cause hospital readmission following discharge to the community from postacute inpatient rehabilitation facilities (IRF).METHODS: The sample included Medicare fee-for-service beneficiaries with stroke, lower extremity joint replacement, and fracture, discharged from IRF in 2011 (N = 75,582). Logistic regression models were used to predict 30-day all-cause readmission. Impairment-specific base models included demographic characteristics and length of stay. Subsequent models included individual comorbidity indices: Tier, Charlson, Elixhauser, functional comorbidity index (FCI), and the hierarchical condition category (HCC). We then added discharge functional status to each model. Results were compared using C-statistics.RESULTS: Thirty-day readmission rates following discharge from an IRF ranged from 6.5% (joint replacement) to 14% (stroke). The C-statistics were 0.53, 0.56, and 0.55 for the base models in the stroke, joint replacement, and fracture groups, respectively. Adding the Tier, Charlson, FCI, or Elixhauser variables increased the C-statistics by 0.03-0.07 across the three impairment categories. Adding the HCC increased the C-statistics by 0.06-0.09. With the addition of discharge functional status in the model, the C-statistics further increased by 0.06-0.09.CONCLUSIONS: Comorbidity indices were weakly associated with 30-day readmission in older adults discharged from postacute inpatient rehabilitation. Adding patient-level functional status to the comorbidity indices further improved the discriminatory ability to predict readmission in our sample.

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